The development of artificial intelligence has functioned as a trigger in the technological world. Things that were previously simply a figment of our imagination are now becoming a reality. A good example is the creation makes self-driving automobile. There are days when you can work or even sleep in your car and yet arrive safely at your destination without touching the steering wheel or accelerator. This research presents a practical model of a self-driving car that can travel from one location to another or on a variety of tracks, including curved, straight, and curved tracks directly followed by curved tracks. Images from the real environment are sent to convolutional neural network via a camera module positioned on the top of the automobile, which can predict any of the following guidelines: right or left, forward or stop, after which an Arduino signal is sent to the remote-controlled car's controller, and the automobile goes to required destination without help of human participation.


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    Titel :

    Convolutional Neural Network Based on Self-Driving Autonomous Vehicle (CNN)


    Weitere Titelangaben:

    Lecture Notes on Data Engineering and Communications Technologies


    Beteiligte:
    Raj, Jennifer S. (Herausgeber:in) / Kamel, Khaled (Herausgeber:in) / Lafata, Pavel (Herausgeber:in) / Babu Naik, G. (Autor:in) / Ameta, Prerit (Autor:in) / Baba Shayeer, N. (Autor:in) / Rakesh, B. (Autor:in) / Kavya Dravida, S. (Autor:in)


    Erscheinungsdatum :

    24.02.2022


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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